The process of building Knowledge Graphs is essential for organizations seeking to organize, structure, and extract actionable insights from their data. However, traditional methods of constructing Knowledge Graphs are often slow, expensive, and complex, requiring...
In the era of data-driven decision-making, Knowledge Graphs (KGs) have emerged as pivotal tools for structuring, organizing, and interconnecting vast amounts of information. From enhancing search engine capabilities to powering AI-driven insights, Knowledge Graphs...
Verticalizing AI21’s Jamba 1.5 with Bitext Synthetic Text Efficiency and Benefits of Verticalizing LLMs – The Case of Jamba 1.5 Mini The verticalization of Large Language Models (LLMs) is transforming the way businesses implement AI-based solutions. By adapting...
A robust discussion persists within the technical and academic communities about the suitability of LLMs for tasks like Named Entity Recognition (NER). While LLMs have demonstrated extraordinary capabilities across a wide range of language-related tasks, several...
On November 19, the Beyond Search Web log published a brief analysis of our multilingual NER (Named Entity Recognition system) technology. The post highlighted the challenges of handling Chinese personal names in English to enable accurate and consistent...
Getting GPT to Answer Consistently and with Style GPT, like other generative models, tends to provide disparate answers for the same question. Sometimes answers vary only slightly, but sometimes they are very inconsistent or even contradictory. Behavior of Standard...
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